68 citations · 72 across the 12 of their papers we have counts for
12 papers
One Model, Multiple Goals: Adaptive Multi-Objective Learning for E-commerce Dialogue Systems
Mingzhe Li, Jing Xiang, Enguo Zhou +5
Dialogue systems in e-commerce scenarios often need to satisfy multiple objectives: accurately reasoning over user profiles (e.g., eligibility, credit limit) to ensure correct deci…
SenWave: A Fine-Grained Multi-Language Sentiment Analysis Dataset Sourced from COVID-19 Tweets
Qiang Yang, Xiuying Chen, Changsheng Ma +3
The global impact of the COVID-19 pandemic has highlighted the need for a comprehensive understanding of public sentiment and reactions. Despite the availability of numerous public…
Cross-Lingual Pitfalls: Automatic Probing Cross-Lingual Weakness of Multilingual Large Language Models
Zixiang Xu, Yanbo Wang, Yue Huang +4
Large Language Models (LLMs) have achieved remarkable success in Natural Language Processing (NLP), yet their cross-lingual performance consistency remains a significant challenge.…
On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective
Yue Huang, Chujie Gao, Siyuan Wu +63
Generative Foundation Models (GenFMs) have emerged as transformative tools. However, their widespread adoption raises critical concerns regarding trustworthiness across dimensions.…
Adaptive Distraction: Probing LLM Contextual Robustness with Automated Tree Search
Yanbo Wang, Zixiang Xu, Yue Huang +6
Large Language Models (LLMs) often struggle to maintain their original performance when faced with semantically coherent but task-irrelevant contextual information. Although prior…
Shaping the Safety Boundaries: Understanding and Defending Against Jailbreaks in Large Language Models
Lang Gao, Jiahui Geng, Xiangliang Zhang +2
Jailbreaking in Large Language Models (LLMs) is a major security concern as it can deceive LLMs to generate harmful text. Yet, there is still insufficient understanding of how jail…
AutoBench-V: Can Large Vision-Language Models Benchmark Themselves?
Han Bao, Yue Huang, Yanbo Wang +7
Large Vision-Language Models (LVLMs) have become essential for advancing the integration of visual and linguistic information. However, the evaluation of LVLMs presents significant…
ScholarChemQA: Unveiling the Power of Language Models in Chemical Research Question Answering
Xiuying Chen, Tairan Wang, Taicheng Guo +7
Question Answering (QA) effectively evaluates language models' reasoning and knowledge depth. While QA datasets are plentiful in areas like general domain and biomedicine, academic…
Advanced Framework for Animal Sound Classification With Features Optimization
Qiang Yang, Xiuying Chen, Changsheng Ma +2
The automatic classification of animal sounds presents an enduring challenge in bioacoustics, owing to the diverse statistical properties of sound signals, variations in recording…
Multi-Intent Attribute-Aware Text Matching in Searching
Mingzhe Li, Xiuying Chen, Jing Xiang +6
Text matching systems have become a fundamental service in most searching platforms. For instance, they are responsible for matching user queries to relevant candidate items, or re…
Large Language Model based Multi-Agents: A Survey of Progress and Challenges
Taicheng Guo, Xiuying Chen, Yaqi Wang +5
Large Language Models (LLMs) have achieved remarkable success across a wide array of tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used as a…
ReactionTeam: Teaming Experts for Divergent Thinking Beyond Typical Reaction Patterns
Taicheng Guo, Changsheng Ma, Xiuying Chen +6
Reaction prediction, a critical task in synthetic chemistry, is to predict the outcome of a reaction based on given reactants. Generative models like Transformer have typically bee…